Lile Cai

According to our database, Lile Cai authored at least 17 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Exploring Diversity-Based Active Learning for 3D Object Detection in Autonomous Driving.

Jinpeng Lin, Zhihao Liang, Shengheng Deng, Lile Cai, Tao Jiang, Tianrui Li, Kui Jia, Xun Xu

IEEE Trans. Intell. Transp. Syst., November, 2024

Revisiting pretraining for semi-supervised learning in the low-label regime.

Xun Xu, Jingyi Liao, Lile Cai, Manh Cuong Nguyen, Kangkang Lu, Wanyue Zhang, Yasin Yazici, Chuan Sheng Foo

Neurocomputing, January, 2024

Label-Efficient Point Cloud Semantic Segmentation: A Holistic Active Learning Approach.

Xian Shi, Lile Cai, Ke Chen, Chuan Sheng Foo, Kui Jia, Xun Xu

World Sci. Annu. Rev. Artif. Intell., 2024

Hybrid Active Learning with Uncertainty-Weighted Embeddings.

Yinan He, Lile Cai, Jingyi Liao, Chuan-Sheng Foo

Trans. Mach. Learn. Res., 2024

The Initialization Factor: Understanding its Impact on Active Learning for Analog Circuit Design.

Sezin Kircali Ata, Zhi-Hui Kong, Anusha James, Lile Cai, Kiat Seng Yeo, Khin Mi Mi Aung, Chuan Sheng Foo, Ashish James

Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

2022

Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous Driving.

Zhihao Liang, Xun Xu, Shengheng Deng, Lile Cai, Tao Jiang, Kui Jia

CoRR, 2022

Revisiting Pretraining for Semi-Supervised Learning in the Low-Label Regime.

Xun Xu, Jingyi Liao, Lile Cai, Cuong Manh Nguyen, Kangkang Lu, Wanyue Zhang, Yasin Yazici, Chuan Sheng Foo

CoRR, 2022

Exploring Active Learning for Semiconductor Defect Segmentation.

Lile Cai, Ramanpreet Singh Pahwa, Xun Xu, Jie Wang, Richard Chang, Lining Zhang, Chuan-Sheng Foo

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021

Exploring Spatial Diversity for Region-Based Active Learning.

Lile Cai, Xun Xu, Lining Zhang, Chuan-Sheng Foo

IEEE Trans. Image Process., 2021

Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach.

Xian Shi, Xun Xu, Ke Chen, Lile Cai, Chuan Sheng Foo, Kui Jia

CoRR, 2021

Revisiting Superpixels for Active Learning in Semantic Segmentation With Realistic Annotation Costs.

Lile Cai, Xun Xu, Jun Hao Liew, Chuan Sheng Foo

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2019

TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks.

Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo, Jie Lin, Vijay Ramaseshan Chandrasekhar, Mohamed M. Sabry Aly

Proceedings of the 2019 IEEE/ACM International Symposium on Low Power Electronics and Design, 2019

MaxpoolNMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors.

Lile Cai, Bin Zhao, Zhe Wang, Jie Lin, Chuan Sheng Foo, Mohamed M. Sabry Aly, Vijay Chandrasekhar

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2017

A two-level clustering approach for multidimensional transfer function specification in volume visualization.

Lile Cai, Binh P. Nguyen, Chee-Kong Chui, Sim Heng Ong

Vis. Comput., 2017

Anomaly detection in thermal images using deep neural networks.

Lile Cai, Yiqun Li

Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2015

Rule-Enhanced Transfer Function Generation for Medical Volume Visualization.

Lile Cai, Binh P. Nguyen, Chee-Kong Chui, Sim Heng Ong

Comput. Graph. Forum, 2015

2013

Automatic transfer function design for medical visualization using visibility distributions and projective color mapping.

Lile Cai, Wei-Liang Tay, Binh P. Nguyen, Chee-Kong Chui, Sim Heng Ong

Comput. Medical Imaging Graph., 2013